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在患者教育中利用生成性人工智能模型对下静脉卡瓦过器的患者教育

Som P Singh¹, Aleena Jamal², Farah Qureshi³

¹Department of Internal Medicine, University of Missouri Kansas City School of Medicine, Kansas City, MO 64108, USA.

Clinics and practice

|August 28, 2024

概括

微软Copilot在下静脉 (IVC) 过器上生成了比ChatGPT更易于阅读的患者教育材料. 然而,这两种人工智能工具都不符合美国推的患者理解阅读等级水平.

科学领域:

医疗教育医学教育
医疗保健中的人工智能
血管外科血管外科

背景情况:

下静脉膜 (IVC) 过器对于控制静脉血栓塞栓症至关重要.
由于越来越多地使用IVC过器,有效的患者教育至关重要.
在IVC过器上,人工智能生成的教育内容的可读性在很大程度上是未知的.

研究的目的:

评估AI模型生成的IVC过器上的患者教育材料的可读性.
为了比较来自ChatGPT和微软Copilot的内容的可读性得分.

主要方法:

使用了Flesch阅读易度 (FRE),Flesch-Kincaid和炮雾指数.
分析了由ChatGPT和微软Copilot生成的关于下静脉卡瓦 (IVC) 过器的教育材料.
在两个AI队伍之间比较可读性指标.

主要成果:

与ChatGPT (17.76 ± 1.62) 相比,微软的Copilot显示了较低的平均枪雾得分 (11.58 ± 1.55).
在AI队伍之间观察到Flesch阅读易度得分的统计学上显著差异 (p = 8.70408 × 10^-8).
这两种AI模型都产生了不符合美国推的阅读水平的内容.

结论:

微软Copilot在IVC过器上提供了比ChatGPT更容易阅读的患者教育材料.
目前用于IVC过器的AI生成内容需要改进,以满足美国标准的教育阅读水平.
需要进一步的研究来优化人工智能工具,以便在血管医学中获得患者信息.

关键词:

生成型的人工智能 (GAI)提高健康素养提高健康素养下 vena cava 的过器是下静脉的过器.患者教育患者教育可读性可读性

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